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## Models
FLUX.1 Fill introduces advanced inpainting and outpainting capabilities. It allows for seamless edits that integrate naturally with existing images.
| Name | HuggingFace repo | License | sha256sum |
| ------------------- | -------------------------------------------------------- | --------------------------------------------------------------------- | ---------------------------------------------------------------- |
| `FLUX.1 Fill [dev]` | https://huggingface.co/black-forest-labs/FLUX.1-Fill-dev | [FLUX.1-dev Non-Commercial License](model_licenses/LICENSE-FLUX1-dev) | 03e289f530df51d014f48e675a9ffa2141bc003259bf5f25d75b957e920a41ca |
| `FLUX.1 Fill [pro]` | Only available in our API. |
## Examples
## Open-weights usage
The weights will be downloaded automatically from HuggingFace once you start one of the demos. To download `FLUX.1 Fill [dev]`, you will need to be logged in, see [here](https://huggingface.co/docs/huggingface_hub/guides/cli#huggingface-cli-login). Alternatively, if you have downloaded the model weights manually from [here](https://huggingface.co/black-forest-labs/FLUX.1-Fill-dev), you can specify the downloaded paths via environment variables:
```bash
export FLUX_DEV_FILL=<path_to_flux_dev_fill_sft_file>
export AE=<path_to_ae_sft_file>
```
For interactive sampling run
```bash
python -m src.flux.cli_fill --loop
```
Or to generate a single sample run
```bash
python -m src.flux.cli_fill \
--img_cond_path <path_to_input_image> \
--img_cond_mask <path_to_input_mask>
```
The input_mask should be an image of the same size as the conditioning image that only contains black and white pixels; see [an example mask](../assets/cup_mask.png) for [this image](../assets/cup.png).
We also provide an interactive streamlit demo. The demo can be run via
```bash
streamlit run demo_st_fill.py
```
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